Triple

T22336967
Position Surface form Disambiguated ID Type / Status
Subject Arledge E552174 entity
Predicate hasNotableBearer P458 FINISHED
Object Roone Arledge NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Roone Arledge | Statement: [Arledge, hasNotableBearer, Roone Arledge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roone Arledge
Context triple: [Arledge, hasNotableBearer, Roone Arledge]
  • A. Roone Arledge chosen
    Roone Arledge was an influential American television executive and producer who revolutionized sports broadcasting and later led ABC News, pioneering formats like Monday Night Football and modern TV news magazines.
  • B. Don Hewitt
    Don Hewitt was an American television news producer best known for pioneering modern TV newsmagazine journalism.
  • C. Chet Huntley
    Chet Huntley was a prominent American television newscaster best known as one half of the influential NBC evening news team "The Huntley–Brinkley Report" during the 1950s and 1960s.
  • D. Arthur Kallet
    Arthur Kallet was an American engineer, consumer advocate, and co-founder of the influential product-testing magazine Consumer Reports.
  • E. Burt Mustin
    Burt Mustin was an American character actor known for his numerous supporting roles in film and television from the 1950s through the 1970s, often portraying kindly elderly men.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e11e494eec81909c4d2d51f69499d9 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f157804e60819094e2a903ace6f4b2 completed April 29, 2026, 12:57 a.m.
Created at: April 16, 2026, 8:43 p.m.